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Journal Article

Citation

Bisht LS, Tiwari G, Rao KR, Jha KN. Adv. Transp. Stud. 2022; (SI 3): 45-58.

Copyright

(Copyright © 2022, Arcane Publishers)

DOI

unavailable

PMID

unavailable

Abstract

The study aims to evaluate the risk of RTC on the selected intercity expressway in India. An exploratory data analysis technique was employed to ascertain crash characteristics. Random parameter negative binomial modelling approaches were used to account for segment-specific unobserved heterogeneity on the 168 km intercity six-lane expressway. According to the revealed crash characteristics, rear-end crashes had the highest proportion of total crashes. Pedestrians' fatality was also significant, a unique characteristic of expressway crashes in low-and-middle-income countries (LMICs) like India. In the case of a hit pedestrian fatal crash, the identity of the impacting vehicle was unknown. The crashes involving median and guardrails also substantially contributed to the total crashes. Cars and trucks were involved in most of the crashes as striking vehicles. Cars as striking vehicles caused the highest pedestrian fatalities. Single-vehicle crashes (SVC) also had a substantial proportion of the total crashes. Temporal crash characteristics reveal that nighttime crashes were slightly higher than daytime crashes. Model results showed that segments with attributes such as the presence of hazards, presence of access location and underpasses, vertical alignment length, horizontal alignment radius, horizontal curve length and high AADT have a high risk of fatal crashes. In contrast, the segments with the attributes such as the presence of a village or settlement, vertical alignment gradient, vertical curve length and speed are negatively associated with the fatal crashes. The effect of these variables was consistent across all the developed models. The statistically significant random parameters are Speed, AADT and vertical curve length. The random parameter negative binomial (RPNB) and correlated random parameter negative binomial (CRPNB) performed better than the fixed parameter negative binomial (FPNB) model. The findings from this study are likely to help the decision-makers and engineers to calibrate the expressway design, mainly when it passes through the villages or settlements.


Language: en

Keywords

Analysis; Case Study; Crash Factors; Crashes; Road Safety

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